A reference-frequency-independent detection statistic for eccentric binary mergers is introduced and applied to GW200105, yielding ln B ≤ 0.9 in favor of the eccentric aligned-spin model over the quasi-circular precessing model.
A Triple Origin for the Heavy and Low-Spin Binary Black Holes Detected by LIGO/Virgo
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abstract
We explore the masses, merger rates, eccentricities, and spins for field binary black holes driven to merger by a third companion through the Lidov-Kozai mechanism. Using a population synthesis approach, we model the creation of stellar-mass black hole triples across a range of different initial conditions and stellar metallicities. We find that the production of triple-mediated mergers is enhanced at low metallicities by a factor of ~100 due to the lower black hole natal kicks and reduced stellar mass loss. These triples naturally yield heavy binary black holes with near-zero effective spins, consistent with most of the mergers observed to date. This process produces a merger rate of between 2 and 25 Gpc^-3 yr^-1 in the local universe, suggesting that the Lidov-Kozai mechanism can potentially explain all of the low-spin, heavy black hole mergers observed by Advanced LIGO/Virgo. Finally, we show that triples admit a unique eccentricity and spin distribution that will allow this model to be tested in the near future.
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Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.
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A universal framework to identify eccentric binary mergers: GW200105 case study
A reference-frequency-independent detection statistic for eccentric binary mergers is introduced and applied to GW200105, yielding ln B ≤ 0.9 in favor of the eccentric aligned-spin model over the quasi-circular precessing model.
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Biased parameter inference of eccentric, spin-precessing binary black holes
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.